A comprehensive, hands-on course teaching prompt engineering specifically designed for Automation Testers, Manual QA Engineers, and Software Developers. Learn how to leverage ChatGPT and AI agents to accelerate testing, development, and code quality.
- ✅ Automation Testers - Learn to generate test automation code, frameworks, and utilities
- ✅ Manual QA Engineers - Master test case generation, bug reports, and test strategies
- ✅ Software Developers - Accelerate development with AI-powered code generation and refactoring
- ✅ DevOps Engineers - Optimize CI/CD pipelines and testing workflows
- ✅ QA Managers - Understand AI capabilities for team productivity
- 🤖 Fundamentals of prompt engineering and AI interaction
- 📝 Generate comprehensive test cases from requirements
- 🔬 Create test automation code (Selenium, Playwright, API tests)
- 🐛 Write better bug reports and analyze failures
- 💻 Generate and refactor production code
- 🤝 Build AI agents for autonomous testing and development
- 🎨 Design efficient testing strategies with AI
- 🚀 Integrate AI into your daily workflow
- What is Prompt Engineering?
- ChatGPT and AI Agents Overview
- Setting Up Your Environment
- Basic Prompt Structure (Role, Context, Task, Format, Constraints)
- Parameters and Temperature Settings
- Best Practices and Optimization
- Test Case Generation with AI
- Bug Report Generation
- Test Scenario Creation
- Edge Case Identification
- Test Automation Code Generation (Selenium, Playwright, Cypress)
- Test Data Generation
- API Testing with AI
- Test Framework Development
- Code Generation and Refactoring
- Code Review and Debugging
- Documentation Generation
- Design Patterns and Architecture
- Chain-of-Thought Prompting
- Few-Shot Learning
- Role-Based Prompting
- Context Management
- Understanding AI Agents
- Building Testing Agents
- Agent-Based Automation
- CI/CD Integration
- Project 1: Automated Test Suite Generator
- Project 2: Bug Triage Assistant
- Project 3: Code Review Bot
- Project 4: Test Data Generator
- Security Considerations
- Ethical AI Usage
- Quality Assurance of AI Outputs
- Continuous Learning
- Basic understanding of software testing OR development
- Computer with internet connection
- Text editor or IDE (VS Code recommended)
- ChatGPT account (free tier works)
- Python 3.9+ (for coding exercises)
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Clone the repository
git clone https://github.com/pandiyarajk/prompt-engineering.git cd prompt-engineering-course -
Set up Python environment (optional, for coding exercises)
python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt
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Configure API access (optional)
cp .env.example .env # Edit .env and add your OpenAI API key -
Start learning!
# Navigate to Module 1 cd modules/module-1-introduction
For Manual QA:
Module 1 → Module 2 → Module 3 → Module 6 → Module 7 → Projects 1 & 2
For Automation Engineers:
Module 1 → Module 2 → Module 4 → Module 6 → Module 7 → All Projects
For Developers:
Module 1 → Module 2 → Module 5 → Module 6 → Module 7 → Projects 3 & 4
For Complete Mastery:
All Modules in order → All Projects → Practice Exercises
prompt-engineering-course/
├── modules/ # Course modules
│ ├── module-1-introduction/
│ ├── module-2-fundamentals/
│ ├── module-3-manual-qa/
│ ├── module-4-automation-testing/
│ ├── module-5-developers/
│ └── module-7-ai-agents/
├── projects/ # Hands-on projects
│ ├── project-1-test-suite-generator/
│ └── project-2-bug-triage-assistant/
├── project-answers/ # Reference implementations
│ ├── project-1-test-suite-generator/
│ └── project-2-bug-triage-assistant/
├── exercises/ # Practice exercises
│ └── practice-prompts.md
├── resources/ # Additional resources
├── examples/ # Example prompts and outputs
└── templates/ # Reusable prompt templates
- 9 modules covering beginner to advanced topics
- 50+ lessons with practical examples
- 100+ ready-to-use prompt templates
- 4 real-world projects
- Build actual tools you can use
- Portfolio-ready implementations
- 50+ practice prompts
- Progressive difficulty
- Answer keys and explanations
- Tailored examples for QA and developers
- Domain-specific use cases
- Real-world scenarios
- Python, Selenium, Playwright
- REST APIs, FastAPI
- CI/CD integration
- Latest AI tools and techniques
After completing this course, you will be able to:
- ✅ Write effective prompts for any testing or development task
- ✅ Generate comprehensive test cases 10x faster
- ✅ Create test automation code with AI assistance
- ✅ Build custom AI agents for testing workflows
- ✅ Refactor and improve existing code efficiently
- ✅ Debug issues faster with AI-powered analysis
- ✅ Create testing frameworks and utilities
- ✅ Integrate AI into CI/CD pipelines
- ✅ Review code with AI assistance
- ✅ Generate technical documentation automatically
Act as a Senior QA Engineer. Create comprehensive test cases for a user
registration feature with email, password, and 2FA. Include positive,
negative, security, and edge cases. Format as a table with Test ID,
Description, Steps, Expected Result, and Priority.
Act as a Test Automation Engineer expert in Selenium with Python.
Create a complete page object model for a login page with email,
password, and remember me checkbox. Include explicit waits, error
handling, and pytest integration. Follow PEP 8 standards.
Act as a Senior Software Engineer. Review this test automation code for:
- Code quality and maintainability
- Best practices violations
- Error handling gaps
- Performance issues
Provide specific recommendations with code examples.
[Code here]
Build a CLI tool that generates complete test suites from requirements documents.
Skills: Prompt engineering, Python, OpenAI API, test design
Create an AI system that analyzes bugs, classifies severity, detects duplicates, and suggests fixes.
Skills: NLP, classification, API integration, web development
Build a bot that automatically reviews code and provides feedback.
Skills: Code analysis, GitHub integration, AI agents
Create a tool that generates realistic test data for various scenarios.
Skills: Data generation, Faker library, AI prompts
- Course Discussion Forum (link)
- Discord Community (link)
- Weekly Office Hours (link)
We welcome contributions! Here's how you can help:
- Report Issues: Found a bug or typo? Open an issue
- Suggest Improvements: Have ideas? Create a feature request
- Submit Examples: Share your prompts and results
- Create Content: Add new modules or exercises
- Review PRs: Help review contributions
See CONTRIBUTING.md for details.
This course is licensed under the MIT License - see the LICENSE file for details.
- OpenAI for ChatGPT and GPT-5.2 API
- The testing and development community
- All contributors and students
- Open source projects that inspired this course
- Email: [email protected]
- Twitter: @pandiyarajk
- LinkedIn: Coming soon.
If you find this course helpful, please:
- ⭐ Star this repository
- 🐦 Share on social media
- 📝 Write a review
- 🤝 Contribute to the project
- Modules: 9
- Lessons: 50+
- Projects: 4
- Exercises: 50+
- Prompt Templates: 100+
- Estimated Time: 40-60 hours
- Level: Beginner to Advanced
- ✅ Core modules complete
- ✅ 4 hands-on projects
- ✅ Practice exercises
- ✅ Prompt templates library
- 🔜 Video tutorials
- 🔜 Interactive exercises
- 🔜 Certification program
- 🔜 Advanced AI agents module
- 📅 LangChain deep dive
- 📅 Custom AI model training
- 📅 Enterprise use cases
- 📅 Mobile testing with AI
Ready to master prompt engineering?
- Start with Module 1: Introduction to Prompt Engineering
- Track Your Progress: [Progress Tracker]
Let's build the future of testing and development together! 🚀